SOTAVerified

Density Estimation

The goal of Density Estimation is to give an accurate description of the underlying probabilistic density distribution of an observable data set with unknown density.

Source: Contrastive Predictive Coding Based Feature for Automatic Speaker Verification

Papers

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Showing 751–800 of 1394 papers

TitleStatusHype
Towards Zero and Few-shot Knowledge-seeking Turn Detection in Task-orientated Dialogue SystemsCode0
Exploring the Training Robustness of Distributional Reinforcement Learning against Noisy State ObservationsCode0
Stationary Density Estimation of Itô Diffusions Using Deep Learning—0
On the use of Wasserstein metric in topological clustering of distributional data—0
Computing on Functions Using Randomized Vector Representations—0
Sharp regret bounds for empirical Bayes and compound decision problems—0
Estimation of Bivariate Structural Causal Models by Variational Gaussian Process Regression Under Likelihoods Parametrised by Normalising Flows—0
Deep Dive into Semi-Supervised ELBO for Improving Classification Performance—0
Benchmarking high-fidelity pedestrian tracking systems for research, real-time monitoring and crowd control—0
Efficient training of lightweight neural networks using Online Self-Acquired Knowledge Distillation—0
A survey on Bayesian inference for Gaussian mixture model—0
Neural density estimation and uncertainty quantification for laser induced breakdown spectroscopy spectra—0
First Order Locally Orderless Registration—0
Kernel Density Estimation by Stagewise Algorithm with a Simple Dictionary—0
Data-driven deep density estimationCode0
Boundary of Distribution Support Generator (BDSG): Sample Generation on the Boundary—0
Quantum Measurement Classification with Qudits—0
ByPE-VAE: Bayesian Pseudocoresets Exemplar VAECode0
Constrained Sampling from a Kernel Density Estimator to Generate Scenarios for the Assessment of Automated Vehicles—0
MD-split+: Practical Local Conformal Inference in High Dimensions—0
Short-term probabilistic photovoltaic power forecast based on deep convolutional long short-term memory network and kernel density estimation—0
PSD Representations for Effective Probability Models—0
Identifying High Accuracy Regions in Traffic Camera Images to Enhance the Estimation of Road Traffic Metrics: A Quadtree-Based Method—0
ADAVI: Automatic Dual Amortized Variational Inference Applied To Pyramidal Bayesian Models—0
Stratified Learning: A General-Purpose Statistical Method for Improved Learning under Covariate Shift—0
Low-rank Characteristic Tensor Density Estimation Part II: Compression and Latent Density EstimationCode0
Learning and Generalization in Overparameterized Normalizing FlowsCode0
A Flow-Based Neural Network for Time Domain Speech Enhancement—0
Multi-Resolution Continuous Normalizing FlowsCode0
Density-Based Bonuses on Learned Representations for Reward-Free Exploration in Deep Reinforcement Learning—0
The DEformer: An Order-Agnostic Distribution Estimating TransformerCode0
GBHT: Gradient Boosting Histogram Transform for Density Estimation—0
Distributed Mean-Field Density Estimation for Large-Scale Systems—0
Tractable Density Estimation on Learned Manifolds with Conformal Embedding FlowsCode0
Density estimation on smooth manifolds with normalizing flows—0
On Memorization in Probabilistic Deep Generative ModelsCode0
Tractable Regularization of Probabilistic Circuits—0
Normalizing Flows for Knockoff-free Controlled Feature SelectionCode0
Semi-supervised Learning with Missing Values Imputation—0
End-To-End Deep Learning-Based Adaptation Control for Frequency-Domain Adaptive System Identification—0
Improving Continuous Normalizing Flows using a Multi-Resolution Framework—0
Field Estimation using Robotic Swarms through Bayesian Regression and Mean-Field Feedback—0
Conformal Embedding Flows: Tractable Density Estimation on Learned Manifolds—0
Physics-Guided Discovery of Highly Nonlinear Parametric Partial Differential EquationsCode0
Manifold Density Estimation via Generalized Dequantization—0
Feedback Interconnected Mean-Field Density Estimation and Control—0
Rectangular Flows for Manifold LearningCode0
Deconvolutional Density Network: Modeling Free-Form Conditional DistributionsCode0
The Dark Machines Anomaly Score Challenge: Benchmark Data and Model Independent Event Classification for the Large Hadron ColliderCode0
Augmented KRnet for density estimation and approximation—0
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All datasetsCIFAR-10MNISTUCI POWERBSDS300ImageNet 32x32UCI GASUCI HEPMASSUCI MINIBOONEOMNIGLOTCaltech-101FreyfacesCelebA-HQ 256x256

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MAFLog-likelihood (nats)3,049—Unverified
2DDPMNLL (bits/dim)3.69—Unverified
3MRCNFNLL (bits/dim)3.54—Unverified
4FFJORDNLL (bits/dim)3.4—Unverified
5RNODENLL (bits/dim)3.38—Unverified
6Pixel CNNNLL (bits/dim)3.03—Unverified
7score SDENLL (bits/dim)2.99—Unverified
8Flow matchingNLL (bits/dim)2.99—Unverified
9Pixel CNN ++NLL (bits/dim)2.92—Unverified
10Image TransformerNLL (bits/dim)2.9—Unverified
#ModelMetricClaimedVerifiedStatus
1DVP-VAENLL77.1—Unverified
2PaddingFlowMMD-L211—Unverified
3FFJORDNLL (bits/dim)0.99—Unverified
4RNODENLL (bits/dim)0.97—Unverified
5IdentityNLL (bits/dim)0.13—Unverified
6MADE MoGLog-likelihood (nats)-1,038.5—Unverified
#ModelMetricClaimedVerifiedStatus
1nMDMALog-likelihood1.78—Unverified
2DDELog-likelihood0.97—Unverified
3B-NAFLog-likelihood0.61—Unverified
4FFJORDLog-likelihood0.46—Unverified
5MADE MoGLog-likelihood0.4—Unverified
6PaddingFlowCD0.14—Unverified
#ModelMetricClaimedVerifiedStatus
1TANLog-likelihood159.8—Unverified
2FFJORDLog-likelihood157.4—Unverified
3B-NAFLog-likelihood157.36—Unverified
4MADE MoGLog-likelihood153.71—Unverified
5PaddingFlowCD0.5—Unverified
#ModelMetricClaimedVerifiedStatus
1GlowNLL (bits/dim)4.09—Unverified
2Image TransformerNLL (bits/dim)3.77—Unverified
3VDMNLL (bits/dim)3.72—Unverified
4i-DODENLL (bits/dim)3.69—Unverified
5MuLANNLL (bits/dim)3.67—Unverified
#ModelMetricClaimedVerifiedStatus
1B-NAFLog-likelihood12.06—Unverified
2DDELog-likelihood9.73—Unverified
3FFJORDLog-likelihood8.59—Unverified
4MADE MoGLog-likelihood8.47—Unverified
5PaddingFlowCD0.89—Unverified
#ModelMetricClaimedVerifiedStatus
1PaddingFlowCD13.8—Unverified
2DDELog-likelihood-11.3—Unverified
3B-NAFLog-likelihood-14.71—Unverified
4FFJORDLog-likelihood-14.92—Unverified
5MADE MoGLog-likelihood-15.15—Unverified
#ModelMetricClaimedVerifiedStatus
1PaddingFlowCD24.5—Unverified
2DDELog-likelihood-6.94—Unverified
3B-NAFLog-likelihood-8.95—Unverified
4FFJORDLog-likelihood-10.43—Unverified
5MADE MoGLog-likelihood-12.27—Unverified
#ModelMetricClaimedVerifiedStatus
1FFJORDNegative ELBO98.33—Unverified
2B-NAFNegative ELBO94.83—Unverified
3DVp-VAENLL89.07—Unverified
4PaddingFlowMMD-L220.3—Unverified
#ModelMetricClaimedVerifiedStatus
1FFJORDNegative ELBO104.03—Unverified
2B-NAFNegative ELBO94.91—Unverified
3PaddingFlowMMD-L217.9—Unverified
#ModelMetricClaimedVerifiedStatus
1FFJORDNegative ELBO4.39—Unverified
2B-NAFNegative ELBO4.33—Unverified
3PaddingFlowMMD-L20.62—Unverified
#ModelMetricClaimedVerifiedStatus
1RNODELog-likelihood1.04—Unverified
#ModelMetricClaimedVerifiedStatus
1MAFLog-likelihood5,872—Unverified
#ModelMetricClaimedVerifiedStatus
1RNODELog-likelihood3.83—Unverified